RedMaxx Data-Driven Management MethodologyMRGPD · Data-Driven Management

Companies that decide with data.

MRGPD is a Brazilian methodology developed by RedMaxx and registered with Brazil's National Library (Fundação Biblioteca Nacional). Built on more than a decade of data-driven management projects, it turns companies into data-driven organizations, from maturity diagnostic to strategic management, with LGPD (Brazil's General Data Protection Law) compliance built in, plus privacy and sovereignty.

Request a Maturity DiagnosticRequest a diagnostic Explore the 6 phases

sequential phases: 6sequential phases
indicators: 90indicators
organizations in the validation: 12organizations in the validation
professionals surveyed: 847professionals surveyed

The problem · data without decisions

Imported management methodologies
don't know Brazil.

methodologies reviewed: 47methodologies reviewed
focus on technology alone: 76%focus on technology alone
lack a complete method: 82%lack a complete method

Your company accumulates data in silos that don't talk to each other: CRM, ERP, spreadsheets, departmental BI. The volume grows, but decisions are still made on intuition; and intuition doesn't scale, can't be audited and doesn't learn.

A systematic review we conducted of 47 international management methodologies showed why off-the-shelf recipes fail: most focus on technology alone, ignore organizational culture and don't cover the full journey, from diagnostic to continuous monitoring.

focus on technology alone and neglect organizational culture: 76%focus on technology alone and neglect organizational culture
don't cover the full journey: from diagnostic to monitoring: 82%don't cover the full journey: from diagnostic to monitoring
were developed for contexts different from Brazil's: 94%were developed for contexts different from Brazil's

And it's not just here. Not even the world's largest organizations have managed it.

execute their data strategy well; in 2021 it was 13%: 12%execute their data strategy well; in 2021 it was 13%
deliver measurable business results with AI: 2%deliver measurable business results with AI
have scaled generative AI, out of the 65% that deployed it: 7%have scaled generative AI, out of the 65% that deployed it

In manufacturing, only 5% have scaled generative AI and 1% use agentic AI, the lowest rate of any sector. And the bottleneck these executives report is not the AI model: it is data quality, separate governance for data and AI, fragmented infrastructure and a shortage of skilled people. None of the ten most-cited obstacles is technology. All of them fit within the five dimensions the DRM-DD measures in a 45-minute conversation.

MIT Technology Review Insights, 2025, in partnership with Databricks · 800 data and technology executives · 12 countries · organizations with annual revenue above US$ 500 million

The methodology · 6 sequential phases

A journey with a beginning, a middle and continuous evolution.

From the initial maturity snapshot to strategic data-driven management: 18 to 24 months to build a culture that doesn't regress. Each phase begins only once the foundation of the previous one is in place, and execution overlaps: the duration shown for each phase is execution time, not calendar time, which is why their sum exceeds the length of the full program.

Phase 01 / 06 · 6 months

Maturity Diagnostic

Where your organization stands today. The DRM-DD is a consultant-led interview of about 45 minutes: 21 core questions cover 90 indicators across 5 dimensions and return an objective index from 0 to 100, the IMDD. Measurement wraps up in two weeks; the full phase runs up to 6 months because it includes an executive debrief, leadership alignment and portfolio prioritization.

Quantitative diagnostic report
Mapping of priority gaps
Recommended modernization projects and opportunities
Roadmap to data-driven maturity

Phase 02 / 06 · 3 to 4 months

Data Governance

Who is accountable for the data. An executive committee, a CDO, data stewards and formal policies, with regulatory compliance built in from the design stage.

Executive Data Committee
CDO and Data Stewards
Governance Policy + LGPD/LAI compliance

Phase 03 / 06 · 6 to 12 months

Cultural Transformation

Teams that think with data. Three training tracks (executive, analytical and operational) to change how the organization makes decisions.

Executive Track (22h)
Analytical Track (64h)
Operational Track (18h)

Phase 04 / 06 · 4 to 8 months

Technology Implementation

The infrastructure behind every decision. Five layers, from ingestion to dashboard, with data sovereignty as the preferred approach.

Data Lake + Data Warehouse
ETL pipelines/APIs
Dashboards and BI

Phase 05 / 06 · 3 months

Data-Driven Strategic Management

Data at the center of decision-making. A KPI framework in four categories: efficiency, effectiveness, transparency and innovation.

KPI framework
4 indicator categories
Evidence-based decision-making routine

Phase 06 / 06 · ongoing

Continuous Evolution

Maturity never stands still. Annual reassessment with the DRM-DD, tracking dashboards and benchmarking; the cycle starts over at a higher level.

Annual DRM-DD reassessment
Tracking dashboards
Continuous improvement

The instrument · DRM-DD

Maturity isn't a matter of opinion.
It's measured.

The DRM-DD is led by a RedMaxx consultant in about 45 minutes: 21 core questions cover 90 indicators across 5 weighted dimensions and return a single index from 0 to 100, the IMDD. The same instrument that diagnoses your company at the start tracks its progress year after year.

The diagnostic report delivers

01
Data-driven maturity: Your IMDD from 0 to 100 across the 5 dimensions: an objective snapshot of today.
02
Evolution roadmap: The prioritized path, level by level, to data-driven management.
03
Project opportunities: Modernization ready to prioritize: AI in decision-making, automation and data integration.
04
AI readiness: The gap between your stated AI ambition and your actual data foundation: what must be in place before scaling.

before afterillustrative profile

Organizational Culture20 ind. · 25%
Data Governance18 ind. · 20%
Technology Capabilities22 ind. · 20%
Analytical Skills16 ind. · 20%
Systems Integration14 ind. · 15%

45 minwith the decision-makers

3 business daysto the report

R$ 0complimentary until Oct 31, 2026

No pause in operations, no tasks for your IT team and no interviewing the entire organization.

Talk to us about the diagnostic

IMDD = (Culture × 0.25 + Governance × 0.20 + Technology × 0.20 + Skills × 0.20 + Integration × 0.15) ÷ 6 × 100

Inside the instrument

A conversation goes in. A defensible number comes out.

The diagnostic is not a form. It is an instrument built in layers, and each layer exists to make the next one verifiable: the final score traces back to the question that produced it.

The conversation

45 minutes with the people who decide, no tasks for your IT team and no system access.

21 core questions

The indicators

Each question scores a cluster of indicators on a 0 to 6 scale.

90 indicators

The dimensions

Culture, Governance, Technology, Skills and Integration, with fixed weights.

25 · 20 · 20 · 20 · 15

The index

The weighted sum becomes a single number, comparable year over year.

IMDD 0 to 100 · 7 levels

The readout

Gaps in order of priority, readiness against standards, opportunities.

23 pages

Interview45 min

Core questions21

Indicators90

Dimensions5

Index0 to 100

No layer is a black box: the report shows the scale, the weight and the question behind each score.

Results · measured in the field

What you gain, in numbers.

Preliminary validation where it is hardest: a pre/post study in 12 public organizations, Brazil's most regulated sector, with 847 respondents and large effect sizes. Convenience sample, no control group, exploratory in nature. What holds up in that environment arrives ready for your company.

01+34%
More evidence-based decisions
A third more decisions cite data instead of intuition; strategy you can defend before the board and the market.
use of data in decisions · 42.0% to 56.3% · d = 1.39 · p = 0.001
02−22.9%
Faster processes
Workflows with reliable data from the source cut rework and shorten the cycle from decision to execution.
processing time · 15.3 to 11.8 days · d = −1.13 · p = 0.002
03+41.2%
Internally perceived transparency
Teams themselves come to see the organization as transparent about decisions, processes and results.
perceived transparency, as rated by public servants · 5.1 to 7.2 · d = 1.77 · p < 0.001
04+27.4%
Satisfaction with processes
Teams more satisfied with day-to-day workflows, measured before and after implementation.
satisfaction with internal processes · 6.2 to 7.9 · d = 1.54 · p < 0.001

Cronbach's α 0.87 to 0.93

CFI 0.93

RMSEA 0.055

Maturity R² 72%

sample 12 organizations · n=847

Preliminary validation: an observational study with no control group and a convenience sample. The results indicate association, not definitive causal attribution. We take rigor seriously, including its limits.

Compliance · by design

Protect the data and open the data.
At the same time.

LGPD is not an obstacle: it is a design requirement. In MRGPD, compliance enters Phase 2 as the foundation of data governance; roles, policies and controls are auditable from day one.

Law 13.709/2018

LGPD

Brazil's General Data Protection Law (LGPD): controller and data protection officer roles defined in the governance structure; data minimization, purpose limitation and anonymization built into data policies from day one, not patched on later.

Phase 2 · Governance

Data Governance

An executive committee, a CDO and data stewards with clear roles: quality, security and responsible use of data as strategic company assets.

The platform · where the method becomes practice

A method without a tool is just paper.
MRGPD runs on RedData.

From DRM-DD data collection to the Phase 6 dashboards, RedMaxx's Brazilian Big Data and AI platform puts every phase of the methodology into practice in your company. Talk to your data and decide in seconds.

Explore the RedData platform

Who delivers · RedMaxx since 2008

The method is ours.
So is the practice.

Founded in 2008 and a pioneer in Big Data and Artificial Intelligence in Brazil's North region, RedMaxx has been developing RedData since 2018 and serves manufacturing, energy, retail and services, from multinationals to companies in the Manaus Industrial Hub. The methodology grew out of that practice: every phase was written from delivered projects, not imported theory.

years in business: 18years in business
project hours: 100k+project hours
clients in 5 states: 80+clients in 5 states

Talk to our team Learn about RedMaxx

Energy · Predictive maintenance

Enel (São Paulo) · Urban Futurability

Challenge: predict failures in automatic reclosers and increase power grid reliability.

Result: RedData integrated with sensors and legacy systems, with predictive AI and real-time dashboards for operations.

Manufacturing · Shop floor

Avell Computadores

Challenge: reduce production waste and bring order to supply chain control.

Result: ERP, sensors and production lines integrated with machine learning; gains in productivity and logistics predictability.

Government · Municipal revenue

City of Manaus, Brazil

Challenge: increase tax revenue without raising tax rates, while tackling underreporting and an inconsistent property registry.

Result: cross-referencing tax data, notary records and satellite imagery; higher property transfer tax (ITBI) and urban property tax (IPTU) revenue, with tax fairness.

RedMaxx and RedData have supported decisions at